Artificial intelligence in revenue management is not just an emerging trend—it is becoming foundational to how leading hotel organizations operate. AI is not an add-on, but rather is core to the science that drives modern commercial strategy.
“The ability to continuously analyze vast, dynamic data sets, including demand signals, market shifts and pricing behaviors, enables revenue decisions to be made with precision and speed that simply aren’t possible with manual or rule-based approaches,” said Klaus Kohlmayr, chief evangelist and development officer, IDeaS.
That said, adoption across the industry is not uniform. Some operators remain cautious, often due to concerns around transparency, trust and how automated systems fit within existing workflows. Kohlmayr noted these are valid considerations, but they also point to a broader shift underway: the most effective AI solutions are built to deliver both automation and explainability, empowering teams to understand, trust and act on the insights generated.
“Importantly, AI is not replacing revenue leaders, it is elevating them,” Kohlmayr said. “By handling the complexity of forecasting, optimization and continuous recalibration, AI frees teams to focus on higher-order strategy: total revenue performance, customer segmentation and cross-functional alignment across the commercial organization.”
Kohlmayr added that from a staffing perspective, this represents evolution—not reduction—as teams become more agile, more strategic and better equipped to manage an increasingly complex landscape.
“Ultimately, the conversation is shifting from whether to adopt AI to how to fully leverage it,” he said. “Organizations that place AI at the core of their revenue strategy will be best positioned to drive sustainable, long-term profitability.”
Generating an Overall Strategy
Hotel operators are already giving AI more pricing control than they realize, said Chris Ellison, vice president of revenue for Brittain Resorts and Hotels.
“Every revenue management system on the market today has some type of AI or machine learning built into it,” Ellison said. “So although operators may not be accepting a full recommendation from their RMS, they are at least generating an overall strategy from AI, and most rate or strategy recommendations are starting at an AI level.”
According to Ellison, the most important next step in AI and RMS will be overcoming integration challenges.
“As more technology companies and more SaaS companies can integrate with an AI model, it's going to open up their PMS to do more than just be a revenue management or property management system,” he said. “That means that going forward, they may be less willing to integrate with other tools that offer what they now offer.”
Their preferred option, Ellison said, is going to be tech companies focusing on what they've now incorporated in their PMS and selling that as a total package.
When it comes to day-to-day usage, Ellison cautioned that over-communication with AI may be a hazard for hoteliers.
“You expect to put a pace report into AI and ask a simple question and get the result you're looking for,” he said. “But I think you're better off uploading raw data as opposed to an actual report. When you upload a report AI will start giving you data points and reciting talking points based on the report instead of the raw data. And you can end up spending as much time explaining what you just gave to AI when you could have just done it yourself in half the time.”
Ellison concluded that AI is valuable and that it's going to be an important part of the future for hoteliers, but it’s important to have an understanding of what it is and what it isn’t.
“So many technology companies say they’re using AI, but how?” he asked. You have the same platform that you had five years ago with a few upgrades and you're suddenly saying that it's AI, but is it really? What truly is AI usage? I think that's the important nuance: understanding what's AI and what's just part of an algorithm designed to produce an answer.”
Stay Within the Guardrails
Jeff Wermager, VP of sales and revenue management at My Place Hotels of America, said My Place is not “handing AI the pricing control keys outright.”
“Through our partnership with IDeaS, the AI-driven system sets day-to-day rates for our hotels automatically, within guardrails our team and the hotel defines,” Wermager said.
However, he noted that extended-stay is a different animal than transient. Corporate accounts, crew business and length-of-stay negotiations still require human judgment that the system currently doesn’t have visibility into.
“I’d describe it as AI owns the high-volume, repeatable pricing decisions; our RM team owns the strategic exceptions—new property ramp-up, market disruptions and negotiated rates,” Wermager told Hotel Management.
As far as which data inputs are driving the most value, competitor pricing certainly plays a factor, but My Place is seeing that the inputs actually moving the needle are local market and demand data.
“We lean on tools like CoStar and Kalibri for granular competitive intelligence, plus our own Market Force platform, now live at 55 properties, to capture hyperlocal demand signals,” Wermager said. “For extended-stay specifically, factors such as active construction and project-based crew lodging demand matter more than typical leisure booking curves. The brands winning with AI right now are the ones feeding it the right local context, not just rate-shopping data.”
According to Wermager, My Place’s revenue management team has actually grown, not shrunk, as automation has expanded. The team has added headcount and promoted from within over the past year. He noted that the job has shifted from “set today’s rate” to interpreting data and coaching GMs and owners on not just revenue strategy, but overall commercial strategy.
“Automation freed our people from manual rate adjustments and we reinvested that time
into franchisee education—training series, tactical playbooks, that kind of thing,” Wermager said. “The skill set moving forward isn’t rate-setting technician, it’s data interpreter and strategic commercial coach.”
Redefining the Revenue Manager's Job
Duetto CTO Robert Matsuoka said that when people ask how much pricing control operators are handing to AI, he thinks the more useful question is what the AI is actually doing.
“At Duetto we draw a hard line between automated execution and autonomous decision-making,” Matsuoka said. “Our forecasting and pricing run on machine-learning models, not agents—a deliberate design choice. The revenue manager sets the guardrails: rate floors and ceilings, competitive positioning. The system optimizes within those bounds, not outside them.”
According to Matsuoka, Duetto offers an automated execution mode for operators who want hands-off management, with manual override available at any point. This means the control question has a specific answer: the operator still owns the decision boundary. The machine works inside it.
“Where AI earns its place today is the work around the decision—reporting, channel balancing, reading signals across a portfolio of properties,” he said. “That's the busywork, not the pricing call itself.”
As far as AI’s effect on the team, Matsuoka noted that automation doesn't remove the revenue manager: It changes what the revenue manager’s job is.
“The old workflow meant hunting for a number across six browser tabs,” Matsuoka said. “The emerging workflow is managing by exception: the system surfaces what needs attention, shows its reasoning, and a person acts.”
Matsuoka added that increasingly that person doesn't have to be a dedicated specialist. A general manager, an owner or a regional director can engage with a pricing decision directly.
“To me that's the real shift,” Matsuoka said. “Not fewer roles, but a wider set of people who can participate in the decision. The headcount story is the wrong one. The audience story is the interesting one.”
Understand the Value of Human Oversight
AI is becoming a powerful tool in hotel revenue management, but most operators are not handing over complete pricing control. Kerry Ranson, president of operations and partner at Raines, said at Raines hotels AI is increasingly used to analyze demand patterns, recommend pricing adjustments and identify opportunities that may not be obvious to a human revenue manager.
However, Ranson noted there is still significant value in human oversight, particularly when it comes to understanding local market dynamics, unconventional demand drivers or one-time events that may not be fully reflected in the data.
“Our work with valued partners like Lighthouse, Kalibri and CoSTR provides our hotels and property teams with AI components that assist us in making efficient, informed decisions while also identifying additional opportunities,” Ranson said.
According to Ranson, the greatest value comes from AI's ability to process large amounts of information simultaneously. Traditional inputs such as historical occupancy, competitor pricing and pace remain important, but today's systems are also incorporating local events, airline capacity, market demand signals and booking behavior across channels.
“The ability to synthesize all of those variables in real time allows us as operators to react faster and with greater confidence than was possible even a few years ago,” he said.
Ranson added that the role of the revenue manager is also evolving. Rather than spending much of their time manually adjusting rates and analyzing spreadsheets, revenue professionals are becoming strategic decision-makers who validate recommendations, identify exceptions and connect revenue strategy to broader business objectives.
“In many ways, AI is not replacing revenue managers; it is elevating their role,” Ranson noted. “The most successful organizations will be those that combine sophisticated technology with experienced operators who understand their markets and can challenge the data when necessary. The future challenge isn't teaching AI how to price rooms; it's teaching hotel systems how to communicate with one another.”
Ranson concluded that the future of revenue management won't be defined by artificial intelligence alone, but it will be determined by how effectively the hotel technology ecosystem works together. As AI continues to evolve, he said, the real opportunity lies in creating seamless connections between PMS, RMS, CRS, CRM, distribution and guest engagement platforms. The operators who gain the greatest competitive advantage will be those who can turn fragmented data into a unified, real-time view of demand, pricing and guest behavior.
“AI will undoubtedly become more predictive and autonomous, but its true potential will only be realized when the industry achieves the level of system integration necessary to support faster, smarter and more informed decision-making,” Ranson said.
This article was originally published in the August/September edition of Hotel Management magazine. Subscribe here.